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An overview of the issues in the airline industry and the role of optimization models and algorithms

Author

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  • A H Ahmed

    (Brunel University)

  • C A Poojari

    (Brunel University)

Abstract

Optimization application has revolutionized the airline industry in all phases of the planning process. One of the current issues facing the airline industry is planning under uncertainty, especially in the context of schedule disruptions. We discuss the robust models and solution algorithms that have been proposed and developed to handle the uncertain parameters. We show that stochastic programming (SP) provides an ideal paradigm for capturing the uncertainties and making robust decisions. We develop and investigate a prototype fleet assignment model formulated as a two-stage SP with recourse.

Suggested Citation

  • A H Ahmed & C A Poojari, 2008. "An overview of the issues in the airline industry and the role of optimization models and algorithms," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 267-277, March.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:3:d:10.1057_palgrave.jors.2602350
    DOI: 10.1057/palgrave.jors.2602350
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    References listed on IDEAS

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    1. Diego Klabjan, 2005. "Large-Scale Models in the Airline Industry," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 163-195, Springer.
    2. Cynthia Barnhart & Timothy S. Kniker & Manoj Lohatepanont, 2002. "Itinerary-Based Airline Fleet Assignment," Transportation Science, INFORMS, vol. 36(2), pages 199-217, May.
    3. Joyce W. Yen & John R. Birge, 2006. "A Stochastic Programming Approach to the Airline Crew Scheduling Problem," Transportation Science, INFORMS, vol. 40(1), pages 3-14, February.
    4. Jay M. Rosenberger & Ellis L. Johnson & George L. Nemhauser, 2003. "Rerouting Aircraft for Airline Recovery," Transportation Science, INFORMS, vol. 37(4), pages 408-421, November.
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    Cited by:

    1. Weihao Ouyang & Xiaohong Zhu, 2023. "Meta-Heuristic Solver with Parallel Genetic Algorithm Framework in Airline Crew Scheduling," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    2. Zhimei Wang & Avishai Ceder, 2017. "Efficient design of freight train operation with double-hump yards," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(12), pages 1600-1619, December.
    3. A T Ernst & M Horn & P Kilby & M Krishnamoorthy, 2010. "Dynamic scheduling of recreational rental vehicles with revenue management extensions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(7), pages 1133-1143, July.

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